Saha, K., Sugar, B., Torous, J., Abrahao, B., Kıcıman, E., & De Choudhury, M. (2019, July). A Social Media Study on the Effects of Psychiatric Medication Use. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 13, No. 01, pp. 440-451)., https://wvvw.aaai.org/ojs/index.php/ICWSM/article/view/3242 A SOCIAL MEDIA STUDY ON THE EFFECTS OF PSYCHIATRIC MEDICATION USE Koustuv Saha , Benjamin Sugar, John Torous, Bruno Abrahao, Emre Kıcıman, Munmun De Choudhury
- One in Six Americans take psychiatric medications - Five of the top 50 drugs sold in the U.S. are psychiatric medications 1
EFFECTS OF PSYCHIATRIC MEDICATIONS • Their mechanism of action poorly understood • Selection of drug treatments is primarily on trial-and-error basis • Understanding the effects of psychiatric medication is important • Clinical trials and reports of adverse events • Limitations with the existing methodologies 2
OUR WORK ...conducts a large-scale social media study of the effects of 49 FDA approved antidepressants across four major families (SSRIs, SNRIs, TCAs, and TeCAs) …adopts a patient-centered approach to study the effects of these drugs as reflected and self-reported in longitudinal social media data 3
PATIENT-CENTERED APPROACH v Historically, psychiatric care has adopted a “Disease-Centered Model” § Neglects the psychoactive effects of drugs v Consequently, a “Drug-Centered Model” has been advocated § Care becomes more collaborative v “Patient-Centered Model” 4
Twitter Data Psy. Drug mentions in Stream Data 2015-16 Self-reports of Intake Account created Personal Drug before 2015? Intake Classifier Compile Treatment & Control Data Control User Data Treatment User Data Construct Before and After samples data Treatment Date Depression Covariates Control Date Psychosis n-grams Anxiety Suicide Stress LIWC Compute covariates on data before treatment dates Treatment Covariates Control Covariates Stratify similar users on propensity scores ….. User strata Depression Outcomes Cognition Psychosis N. Affect P. Affect Anxiety Suicide Compare the outcomes of similar users 5 Relative Treatment Effect (RTE) per drug
DATA I’m taking my first dose of X tonight. First day on X. Dose 1 taken, and I already feel weird from it. Twitter posts Medication Self- List of mentioning intake classifier psychiatric psychiatric (Klein et al. medications My no-med experiment went medications 2017) horribly awry, so I’m starting X 49 medications 601,134 posts 93,275 self- today . by 230,573 intake posts unique users 6
Sertraline Escitalopram Fluoxetine Duloxetine Citalopram Venlafaxine Mirtazapine Paroxetine Amitriptyline Bupropion Buspirone Atomoxetine Desvenlafaxine Doxepin Dosulepin Fluvoxamine Imipramine Vortioxetine Clomipramine 1 2 3 4 10 100 1000 10000 1 2 3 4 5 6 7 8 9 101112 Posts Month 7
TREATMENT AND CONTROL DATASET - Twitter timelines of 23,191 users who self-reported psychiatric medication intake (2015-2016) [Treatment] - Random Twitter user timelines (283,374 users) [Control] 8
STUDY DESIGN • Conduct Observational Study • Adopt a Causal Inference Framework based on Matching • Compare the outcomes of similar (matched) individuals, those exposed to a treatment (psychiatric drug intake), and those who were not. • Use stratified propensity score analysis 9
BEFORE AND AFTER SAMPLES • For Treatment users, the before and after the date of the first intake of medications • For Control users, we simulate placebo dates by non- parametrically assigning dates from the distribution of Treatment dates. 10
MEASURING SYMPTOMATIC OUTCOMES -Affect and Cognition -Depression, Anxiety, Stress, Psychosis, and Suicidal Ideation 11
AFFECT, COGNITION LIWC categories of - positive and negative affect for affect, - cognitive mechanics , causation , certainty, inhibition, discrepancies, negation, and tentativeness for cognition 12
DEPRESSION, ANXIETY, STRESS, PSYCHOSIS, SUICIDAL IDEATION - Supervised learning classifiers trained on Reddit domain-specific datasets - Positive class from r/depression, r/anxiety, r/stress, r/psychosis, r/SuicideWatch - Negative class from 20M Reddit posts gathered from 20 subreddits (eg. r/AskReddit,r/aww, r/movies). 13
MATCHING FOR CAUSAL INFERENCE Covariates: - Social Attributes (#tweets, #followers, #followees, duration on platform, frequency of posting) - Top 2,000 unigrams - Normalized psycholinguistic occurrence of LIWC categories - Baseline mental health status (aggregated use of depression, anxiety, stress, psychosis, and suicidal ideation) 14
PROPENSITY SCORE ANALYSIS • Use logistic regression classifier to µ +/- 2 σ estimate propensity scores on covariates 3 . 0 2 . 5 Density (Users) • 100 strata of equal width of propensity 2 . 0 scores 1 . 5 • Standardized differences to measure 1 . 0 balance of covariates 0 . 5 0 . 0 0 . 0 0 . 2 0 . 4 0 . 6 0 . 8 1 . 0 Propensity Score 15
TREATMENT EFFECT • Relative Treatment Effect (RTE) • Ratio of change in outcome of Tr. And Ct. users per stratum • Individual Treatment Effect (ITE) • Regress on psycholinguistic attributes and outcome in Ct. users • Predict on attributes of matched Tr. users • Ratio of actual (counterfactual) and predicted outcome 16
Suicidal Idn. RELATIVE TREATMENT EFFECT Depression Cognition Psychosis N. Affect P. Affect Anxiety Amitriptyline 0 Atomoxetine Bupropion Buspirone Citalopram 0.5 Clomipramine Desvenlafaxine Dosulepin 1.0 Doxepin Duloxetine Escitalopram Fluoxetine Fluvoxamine 1.5 Imipramine Mirtazapine Nortriptyline Paroxetine 2.0 Sertraline Venlafaxine Vortioxetine 2.5 SSNRI SSRI TCA TeCA 3.0 17
INDIVIDUAL TREATMENT EFFECT • Blues indicate greater likelihood of improvement • Reds indicate greater likelihood of worsening 18
DISCUSSION 19
TAKEAWAYS Social media is an effective sensor to scalably detect • behavioral changes in those who initiate treatment via (self- reported) use of psychiatric medications Observe that people’s online behaviors change in some • unexpected ways following drug intake 20
POLICY AND ETHICS • Potential negative consequences of this work • Ethical complexities • Self-treatment 21
CLINICAL IMPLICATIONS • Patient-Centered Approach to Pharmacological Care • Complementary insights into the effects of drugs • Pre-treatment signals seem to be predictive of individual drug success • Drug Repurposing Low cost and high volume assessments of people’s own reports • and perceptions related to antidepressants’ use 22
TECHNOLOGICAL IMPLICATIONS Technologies for Regulatory Bodies • Technologies for Drug Safety Surveillance • Technologies to support Digital Therapeutics • 23
Saha, K., Sugar, B., Torous, J., Abrahao, B., Kıcıman, E., & De Choudhury, M. (2019, July). A Social Media Study on the Effects of Psychiatric Medication Use. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 13, No. 01, pp. 440-451)., https://wvvw.aaai.org/ojs/index.php/ICWSM/article/view/3242 A Social Media Study on the Effects of Psychiatric Medication Use Thank You @kous2v| koustuv.saha@gatech.edu | koustuv.com
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